Abstract
The traditional oral liquid light inspect method has many defects and deficiencies. In this paper, an automatic oral liquid light inspection machine is designed to implement the detection of visible particles in oral liquid. Initially, the original images are captured, the background noise is removed using the image technique, and then the target image with visual particles and air bubble noise are acquired. Secondly, an adaptive threshold processing algorithm is used to extract moving target. After that, the position of the biggest object in two different images is compared to remove the overlap section. Finally, the real-time detection system to determine whether the biggest object is visual particle is implemented. A large number of experimental results show that the method proposed in this paper is more accurate and quicker than traditional detection method.
Lasheng Yu––This paper has been supported by the cooperation project in industry, education and research of Guangdong province and Ministry of Education of P.R.China (Granted number:2011B090400316).
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Yu, L., Zeng, Y., Huang, Z. (2015). Research on an Intelligent Liquid Lamp Inspector Based on Machine Vision. In: Ali, M., Kwon, Y., Lee, CH., Kim, J., Kim, Y. (eds) Current Approaches in Applied Artificial Intelligence. IEA/AIE 2015. Lecture Notes in Computer Science(), vol 9101. Springer, Cham. https://doi.org/10.1007/978-3-319-19066-2_53
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DOI: https://doi.org/10.1007/978-3-319-19066-2_53
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